Black Seabass Mean Map

Mean sea bass percent larvae contribution.

# load libraries ----
library(tidyverse) # install.packages('tidyverse')
library(raster)
library(leaflet)
select = dplyr::select
stack  = raster::stack

r = raster('G:/Team_Folders/Steph/bsb/mean.tif')

d = data_frame(
  quantity = raster::getValues(r),
  cellid   = 1:length(quantity),
  area_km2 = 8)

d2 = d %>%
  filter(!is.na(quantity)) %>%
  arrange(desc(quantity)) %>%
  mutate(
    pct_quantity     = quantity/sum(quantity)*100,
    cum_pct_quantity = cumsum(quantity/sum(quantity)*100),
    cum_area_km2     = cumsum(area_km2))

#tail(d2) # 7208 km2
#tail(d2$cum_area_km2, 1) # 7208 km2

d3 = d %>%
  left_join(d2, by='cellid')
#summary(d3)

r2 = setValues(r, d3$cum_pct_quantity)

binpal <- colorBin("Spectral", seq(0,100), 10, pretty = FALSE, na.color = "transparent")

leaflet() %>% 
  addTiles() %>%
  addProviderTiles('Esri.OceanBasemap') %>%
  addRasterImage(r2, colors = binpal, opacity = 0.6) %>%
  addMarkers(lat=31.3855157, lng=-80.8843762, popup = "Gray's Reef") %>%
  addLegend(
    pal = binpal, values = seq(0,100),
    title = "cum % larvae")

Red Snapper Mean Map

Mean Red Snapper percent larvae contribution.

# load libraries ----
library(tidyverse) # install.packages('tidyverse')
library(raster)
library(leaflet)
select = dplyr::select
stack  = raster::stack

r = raster('G:/Team_Folders/Steph/rs/mean.tif')

d = data_frame(
  quantity = raster::getValues(r),
  cellid   = 1:length(quantity),
  area_km2 = 8)

d2 = d %>%
  filter(!is.na(quantity)) %>%
  arrange(desc(quantity)) %>%
  mutate(
    pct_quantity     = quantity/sum(quantity)*100,
    cum_pct_quantity = cumsum(quantity/sum(quantity)*100),
    cum_area_km2     = cumsum(area_km2))

#tail(d2) # 7208 km2
#tail(d2$cum_area_km2, 1) # 7208 km2

d3 = d %>%
  left_join(d2, by='cellid')
#summary(d3)

r2 = setValues(r, d3$cum_pct_quantity)

binpal <- colorBin("Spectral", seq(0,100), 10, pretty = FALSE, na.color = "transparent")

leaflet() %>% 
  addTiles() %>%
  addProviderTiles('Esri.OceanBasemap') %>%
  addRasterImage(r2, colors = binpal, opacity = 0.6) %>%
  addMarkers(lat=31.3855157, lng=-80.8843762, popup = "Gray's Reef") %>%
  addLegend(
    pal = binpal, values = seq(0,100),
    title = "cum % larvae")

Scamp Mean Map

Mean Scamp percent larvae contribution.

# load libraries ----
library(tidyverse) # install.packages('tidyverse')
library(raster)
library(leaflet)
select = dplyr::select
stack  = raster::stack

r = raster('G:/Team_Folders/Steph/sp/mean.tif')

d = data_frame(
  quantity = raster::getValues(r),
  cellid   = 1:length(quantity),
  area_km2 = 8)

d2 = d %>%
  filter(!is.na(quantity)) %>%
  arrange(desc(quantity)) %>%
  mutate(
    pct_quantity     = quantity/sum(quantity)*100,
    cum_pct_quantity = cumsum(quantity/sum(quantity)*100),
    cum_area_km2     = cumsum(area_km2))

#tail(d2) # 7208 km2
#tail(d2$cum_area_km2, 1) # 7208 km2

d3 = d %>%
  left_join(d2, by='cellid')
#summary(d3)

r2 = setValues(r, d3$cum_pct_quantity)

binpal <- colorBin("Spectral", seq(0,100), 10, pretty = FALSE, na.color = "transparent")

leaflet() %>% 
  addTiles() %>%
  addProviderTiles('Esri.OceanBasemap') %>%
  addRasterImage(r2, colors = binpal, opacity = 0.6) %>%
  addMarkers(lat=31.3855157, lng=-80.8843762, popup = "Gray's Reef") %>%
  addLegend(
    pal = binpal, values = seq(0,100),
    title = "cum % larvae")

Gag Mean Map

Mean Gag percent larvae contribution.

# load libraries ----
library(tidyverse) # install.packages('tidyverse')
library(raster)
library(leaflet)
select = dplyr::select
stack  = raster::stack

r = raster('G:/Team_Folders/Steph/gg/mean.tif')

d = data_frame(
  quantity = raster::getValues(r),
  cellid   = 1:length(quantity),
  area_km2 = 8)

d2 = d %>%
  filter(!is.na(quantity)) %>%
  arrange(desc(quantity)) %>%
  mutate(
    pct_quantity     = quantity/sum(quantity)*100,
    cum_pct_quantity = cumsum(quantity/sum(quantity)*100),
    cum_area_km2     = cumsum(area_km2))

#tail(d2) # 7208 km2
#tail(d2$cum_area_km2, 1) # 7208 km2

d3 = d %>%
  left_join(d2, by='cellid')
#summary(d3)

r2 = setValues(r, d3$cum_pct_quantity)

binpal <- colorBin("Spectral", seq(0,100), 10, pretty = FALSE, na.color = "transparent")

leaflet() %>% 
  addTiles() %>%
  addProviderTiles('Esri.OceanBasemap') %>%
  addRasterImage(r2, colors = binpal, opacity = 0.6) %>%
  addMarkers(lat=31.3855157, lng=-80.8843762, popup = "Gray's Reef") %>%
  addLegend(
    pal = binpal, values = seq(0,100),
    title = "cum % larvae")

Black Sea Bass Area Graph

Area Required to Attain Target Percent qunatity of Black Sea Bass Larvae

library(tidyverse)
library(raster)
library(plotly)

r = raster('G:/Team_Folders/Steph/bsb/mean.tif')

d = data_frame(
  quantity = raster::getValues(r),
  cellid   = 1:length(quantity),
  area_km2 = 8)

d2 = d %>%
  filter(!is.na(quantity)) %>%
  arrange(desc(quantity)) %>%
  mutate(
    pct_quantity     = quantity/sum(quantity)*100,
    cum_pct_quantity = cumsum(quantity/sum(quantity)*100),
    cum_area_km2     = cumsum(area_km2))

d3 = d %>%
  left_join(d2, by='cellid')
summary(d3)
##    quantity.x        cellid        area_km2.x   quantity.y   
##  Min.   :0.000   Min.   :    1   Min.   :8    Min.   :0.000  
##  1st Qu.:0.003   1st Qu.: 3052   1st Qu.:8    1st Qu.:0.003  
##  Median :0.018   Median : 6102   Median :8    Median :0.018  
##  Mean   :0.018   Mean   : 6102   Mean   :8    Mean   :0.018  
##  3rd Qu.:0.032   3rd Qu.: 9153   3rd Qu.:8    3rd Qu.:0.032  
##  Max.   :0.050   Max.   :12204   Max.   :8    Max.   :0.050  
##  NA's   :11102                                NA's   :11102  
##    area_km2.y     pct_quantity   cum_pct_quantity   cum_area_km2  
##  Min.   :8       Min.   :0.000   Min.   :  0.251   Min.   :   8   
##  1st Qu.:8       1st Qu.:0.014   1st Qu.: 52.570   1st Qu.:2210   
##  Median :8       Median :0.091   Median : 87.151   Median :4412   
##  Mean   :8       Mean   :0.091   Mean   : 73.477   Mean   :4412   
##  3rd Qu.:8       3rd Qu.:0.159   3rd Qu.: 99.205   3rd Qu.:6614   
##  Max.   :8       Max.   :0.251   Max.   :100.000   Max.   :8816   
##  NA's   :11102   NA's   :11102   NA's   :11102     NA's   :11102
d_20 = d2 %>% filter(cum_pct_quantity >= 20) %>% head(1)

d_40 = d2 %>% filter(cum_pct_quantity >=40) %>% head(1)

d_60 = d2 %>% filter(cum_pct_quantity >= 60) %>% head(1)

plot(r)
p = ggplot(d2, aes(y=cum_pct_quantity, x=cum_area_km2)) +
  xlab("Cumulative Area km2") +
  ylab("Cumulative Percent Quantity Larvae") +
  ggtitle("Black Sea Bass 2009 - 2015") +
  geom_point() +
  geom_segment(x=0, xend=d_20$cum_area_km2, y=d_20$cum_pct_quantity, yend=d_20$cum_pct_quantity) +
  geom_segment(x=d_20$cum_area_km2, xend=d_20$cum_area_km2, y=0, yend=d_20$cum_pct_quantity) +
  geom_segment(x=0, xend=d_40$cum_area_km2, y=d_40$cum_pct_quantity, yend=d_40$cum_pct_quantity) +
  geom_segment(x=d_40$cum_area_km2, xend=d_40$cum_area_km2, y=0, yend=d_40$cum_pct_quantity) +
  geom_segment(x=0, xend=d_60$cum_area_km2, y=d_60$cum_pct_quantity, yend=d_60$cum_pct_quantity) +
  geom_segment(x=d_60$cum_area_km2, xend=d_60$cum_area_km2, y=0, yend=d_60$cum_pct_quantity) +
  scale_y_continuous(expand = c(0,0), breaks = c(20,40,60,80,100)) + scale_x_continuous(expand = c(0,0)) +
  theme(panel.grid.minor.x = element_blank())
  # coord_cartesian(xlim = c(0, tail(d$cum_area_km2, 1)), ylim = c(0, 100))

# print(p)
ggplotly(p)

Video

library(vembedr)

embed_youtube(id="wL-nUjYeMXU", width=672, height=480)

Rmarkdown

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